[BioC] New to microarray analysis

Narendra Kaushik kaushiknk at Cardiff.ac.uk
Fri Mar 27 17:42:18 CET 2009

There are web several resources, you could download course material from there. 

A microarray analysis for differential gene expression in the soybean genome using Bioconductor and R
Briefings in Bioinformatics 2007 8 415-431. 

Course material from: 


This will be a good start for you, and there are books. 

Hope this helps


>>> Sean Davis <seandavi at gmail.com> 27/03/2009 15:28 >>>
On Fri, Mar 27, 2009 at 10:38 AM, Philip Twumasi-Ankrah <
nana_kwadwo_derkyi at yahoo.com> wrote:

> I am new to microarray analysis and need help on two fronts:
> 1. Can any one direct me to a resources that provide directions on a how to
> systematically conduct an analysis of differential expression data.
> Something like what the paper by Harrel and others "Tutorial in
> biostatistics,
> multivariate prognostic models: issues in developing models, evaluating
> assumptions and adequacy, and measuring and reducing errors" provides for
> regular biostatistical analysis
> 2. I have this affymetrix hg_u1332a chip data in a 22000 X 62 matrix. The
> columns are different patients and I am seeking suggestions on analysis. My
> goal is to report on informative genes relative to disease under study.

Hi, Philip.  If you take a look at the Bioconductor website, there are a
number of resources in the form of books that are not TOO expensive.  Those
are a good place to start.  Also, you might notice that each of the
bioconductor packages has at least one "vignette", sort of like a manual,
that describes how to use the various packages; these are also fantastic
sources of information.  Finally, for differential expression, there are a
number of packages in bioconductor that can do what you want, but you might
want to start with the limma package.

And just a comment on what you have so far:  a matrix is a poor
representation of microarray data.  You might want to look at the affy and
Biobase packages for the bioconductor approach to dealing with affymetrix


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